Size effects in axially loaded square-section concrete prisms strengthened using carbon fibre reinforced polymer wrapping
Bibliographic record
Abstract
The use of carbon fibre reinforced polymer (CFRP) wrapping to strengthen plain concrete prisms of square cross section was investigated experimentally. The study was aimed at quantifying the increase in axial compressive strength and ductility that can be achieved and assessing the effect of cross-sectional size on the increases. Thirty prisms of three different square cross-sectional sizes (100 mm × 100 mm × 300 mm, 125 mm × 125 mm × 375 mm, 150 mm × 150 mm × 450 mm) were tested. Ten prisms were constructed in each size. Five prisms in each size were left unwrapped as control specimens, and five were wrapped with two layers of unidirectional CFRP laminate. All prisms were loaded in axial compression until failure. Significant increases in strength and ductility were achieved by wrapping. The effectiveness of the wrap, as measured by the percentage increases in strength and peak axial strain, reduced with increasing cross-sectional size. These tests indicate that the use of CFRP wrapping is an effective technique for strengthening and (or) rehabilitating concrete columns. Test results available in the literature by other authors are also summarized. Although these results are highly scattered, they are consistent with the findings of the current tests.Key words: concrete, prism, column, square, rehabilitation, strengthening, FRP, experimental.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".